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---
tags:
- generated_from_trainer
model-index:
- name: results_mt5_xl-sum
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# results_mt5_xl-sum
This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8431
- Rouge1 Fmeasure: 0.6139
- Rouge2 Fmeasure: 0.1189
- Rougel Fmeasure: 0.1997
- Meteor: 0.3315
- Bertscore F1: 0.8418
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0005
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 250
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 Fmeasure | Rouge2 Fmeasure | Rougel Fmeasure | Meteor | Bertscore F1 |
|:-------------:|:------:|:----:|:---------------:|:---------------:|:---------------:|:---------------:|:------:|:------------:|
| 2.6516 | 0.8529 | 500 | 0.9710 | 0.2668 | 0.0484 | 0.1537 | 0.2745 | 0.8284 |
| 1.0475 | 1.7058 | 1000 | 0.8792 | 0.4289 | 0.0884 | 0.1737 | 0.2949 | 0.8278 |
| 0.9413 | 2.5586 | 1500 | 0.8457 | 0.4960 | 0.0865 | 0.1898 | 0.3141 | 0.8339 |
| 0.8711 | 3.4115 | 2000 | 0.8398 | 0.5400 | 0.1121 | 0.1941 | 0.3110 | 0.8397 |
| 0.8235 | 4.2644 | 2500 | 0.8345 | 0.5587 | 0.1022 | 0.2041 | 0.3160 | 0.8388 |
| 0.7797 | 5.1173 | 3000 | 0.8368 | 0.5735 | 0.1036 | 0.2044 | 0.3157 | 0.8344 |
| 0.7401 | 5.9701 | 3500 | 0.8217 | 0.5507 | 0.1133 | 0.1936 | 0.3186 | 0.8366 |
| 0.7022 | 6.8230 | 4000 | 0.8361 | 0.5808 | 0.1118 | 0.2008 | 0.3227 | 0.8406 |
| 0.6796 | 7.6759 | 4500 | 0.8344 | 0.6173 | 0.1277 | 0.1986 | 0.3260 | 0.8407 |
| 0.6523 | 8.5288 | 5000 | 0.8436 | 0.6232 | 0.1186 | 0.2024 | 0.3317 | 0.8398 |
| 0.6385 | 9.3817 | 5500 | 0.8431 | 0.6139 | 0.1189 | 0.1997 | 0.3315 | 0.8418 |
### Framework versions
- Transformers 4.40.0
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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